Fri, 02/09/2018 - 10:30am - 11:30am

Palliative and end-of-life care are special types of healthcare that focus on improving the quality of life of patients who are living with life-threatening illness or nearing their end of life. The primary goal here is to provide various support services to help the patients to maintain an active life and dignity. Assuming there are cost and resource limitations for delivering care within the system, where each care provider can support a limited number of patients, the problem can be defined as finding a set of suitable care providers with a minimum overall cost to match the needs of the maximum number of patients.

In the grand scheme, the whole care system can be seen as a social network consisting of patients and care providers. This representation provides an opportunity to apply social network analysis and machine learning techniques to enhance the topology of the system and improve its efficiency. In this talk, we present a novel computational knowledge-based model to address this problem by extending the agent’s capabilities using the benefits of the network. The primary objective is to optimize a dynamic, personalized care pathway system that will support palliative care within a community eco-system.

Bio:

Pooya Moradian Zadeh received his Ph.D. in Computer Science from the University of Windsor (2014- 2017). Currently, Pooya is a limited term Assistant Professor in the School of Computer Science at the University of Windsor. His primary research is in the area of data mining and data analytics in healthcare systems with focus on the evolution and optimization of complex dynamic social systems. He is specifically interested in designing effective models and algorithms for the resource allocation, clustering and team formation problems in community-based healthcare systems.